
The article lists down the softwares used at different layers in the LinkedIn platform layered architecture.
Presentation Layer
- Dust.js (Client-side templating JS engine)
- Backbone.js (Client-side MVC JS framework)
- JQuery
- YUI Library (UI libraries started by Yahoo engineers)
- Google V8 Engine (Used as server side JS templating engine)
- Node.js (Used in mobile app)
- HTML5 (Used in mobile app)
Business Layer
- Java (Applications such as Profile)
- Grails (Applications such as a Recruiter app)
- JRuby (Applications such as a Skills app)
- Spring (Component Model)
- Scala
Middleware
- Apache Kafka (Distributed entreprise-level messaging system)
Data Layer
- Oracle (RDBMS as primary data store used for writes)
- Espresso (NoSQL data store emerging as primary data store and envisioned to replace Oracle)
- Voldemart (NoSQL data store serving many Read-only pages)
- Zoie (Lucene)
- Bobo (Lucene)
- MySQL
- Databus (Change data capture system)
- Hadoop (Map-Reduce)
Cross-cutting concerns
- Apache Helix (Clustering management)
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http://www.infoq.com/presentations/Data-Infrastructure-LinkedIn is a presentation by Sid Anand (perhaps, qualifies for your Hall of Fame) and is quite informative.
http://www.infoq.com/interviews/12-mar-sid-anand/ is an interview with the same person and he highlights some good reasons for Linkedin to move away from RDBMS and more importantly the migration path